| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: facebook/bart-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: facebook/bart-base |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # BART-model-fine_tuned |
| |
| This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5467 |
| - Rouge1: 58.168 |
| - Rouge2: 45.9825 |
| - Rougel: 54.3562 |
| - Rougelsum: 54.4552 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - gradient_accumulation_steps: 4 |
| - weight_decay: 0.01 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
| | 0.6587 | 1.0 | 563 | 0.6037 | 56.3206 | 44.2624 | 52.832 | 52.8704 | |
| | 0.6162 | 2.0 | 1126 | 0.5719 | 56.8789 | 44.8139 | 53.3803 | 53.4437 | |
| | 0.5815 | 3.0 | 1689 | 0.5560 | 57.6576 | 45.5559 | 53.943 | 54.0187 | |
| | 0.5663 | 4.0 | 2252 | 0.5491 | 57.9815 | 45.9701 | 54.2183 | 54.3077 | |
| | 0.546 | 5.0 | 2815 | 0.5467 | 58.168 | 45.9825 | 54.3562 | 54.4552 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.47.0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
|
|
